Deep Utils
Project description
Deep Utils
This repository contains the most frequently used deep learning modules and functions.
Table of contents
Quick start
-
Install:
# With pip: pip install deep_utils # or from the repo pip install git+https://github.com/pooya-mohammadi/deep_utils.git # or clone the repo git clone https://github.com/pooya-mohammadi/deep_utils.git deep_utils pip install -U deep_utils
-
In python, import deep_utils and instantiate models:
from deep_utils import face_detector_loader, list_face_detection_models # list all the available models first list_face_detection_models() # Create a face detection model using SSD face_detector = face_detector_loader('SSDCV2CaffeFaceDetector')
-
Detect an image:
import cv2 from deep_utils import show_destroy_cv2, Box # Load an image img = cv2.imread(<image path>) # Detect the faces boxes, confidences = face_detector.detect_faces(img) # Draw detected boxes on the image img = Box.put_box(img, boxes) # show the results show_destroy_cv2(img)
References
- Tim Esler's facenet-pytorch repo: https://github.com/timesler/facenet-pytorch
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
deep_utils-0.7.1.tar.gz
(97.9 kB
view hashes)
Built Distribution
deep_utils-0.7.1-py3-none-any.whl
(132.4 kB
view hashes)
Close
Hashes for deep_utils-0.7.1-py3-none-any.whl
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 5e1c7795e4b7972891456b4e91be6bb02cc96ac94e5d6bb7c2a87d44ecd2a65c |
|
| MD5 | cec824f7812a23e844f224948c9ba5dc |
|
| BLAKE2b-256 | 20aeb7e6e6528dbc018a899513302d0845bda4f13e533120382e9bb6798a1190 |
